Robots have been developed for multiple purposes over the last few decades. The most successful robotic applications are fixed-base units, which are programmed to perform single, clearly delineated, relatively simple tasks (such as welding a particular portion of a car body in an assembly line). Recently, some mobile robots have seen commercial success, such as the Roomba—an automated vacuum cleaner suitable for household cleaning.
However, a number of other applications that could potentially make use of robotic devices or unmanned vehicles require operation in much more demanding settings. For example, the military is using a number of unmanned vehicles on land, sea, or in the air. Other industries, such as the railroad industry, also have a number of tasks which are commonly performed and potentially simple enough to expect a machine to be able to achieve routinely. A significant challenge to developing fully automated machines for these settings is that simple tasks often can present difficulties. However, the setting may require achieving perfection or near perfection, e.g., these tasks may need to be performed effectively one hundred percent of the time (e.g., one failure out of millions of operations).
In many current-art approaches, robots are capable of recognizing gross failures or situations in which the robot simply does not recognize any key elements of its environment. At that point, the robot requires a human being to completely take over. Additionally, the robot may have caused other problems (e.g., a railroad robotic vehicle, having gotten badly turned around, could cross over an active track and be hit by or even cause a derailment of moving rail vehicles). Because of this, current robotic systems are either completely remote-controlled, or controlled by relatively “fragile” autonomy, which is cut off whenever the robot encounters a situation that does not meet its operational parameters.
Previous approaches have sought to improve one or more aspects of robotic operation and interaction between robotic devices and users. One approach proposes a multi-robot control interface, which allows a user to control multiple robotic devices using a single user interface. Another approach seeks to provide power saving features in a robot via a peripheral device including a controller having an active mode and a hibernation mode. Still another approach seeks to use a graphical interface and a control intermediary to analyze and determine a task-oriented autonomy level for a robot.